Systems and methods for providing animal health, nutrition, and/or wellness recommendations

ABSTRACT

The present disclosure is directed to systems and methods for preparing nutrition, health, and/or wellness recommendations for an animal. The systems and methods involve collecting data from the animal, analyzing the data, and providing the nutrition, health, and/or wellness recommendation based upon the analyzed data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/111,101 filed Dec. 3, 2020, which is a continuation of U.S. patentapplication Ser. No. 14/793,304 filed Jul. 7, 2015, now U.S. Pat. No.10,922,995 which issued Feb. 16, 2021, which claims priority to U.S.Provisional Patent Application No. 62/021,763 filed Jul. 8, 2014, thecontents of which are incorporated herein by reference in theirentireties.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to systems and methods for theprovision of recommendations on improved nutrition, health, and/orwellness protocols using animal health, behavior, and/or environmentalinformation.

BACKGROUND

Various approaches for animal health and behavior monitoring are knownin the art. However, most approaches do not provide adequateinterpretation of the data derived from such monitored data, nor is theinterpretation communicated to the appropriate individuals in the formof insights about, and recommendations for, the animal.

SUMMARY OF THE DISCLOSURE

Among the various aspects of the present disclosure is the provision ofmethods of preparing a nutrition, health, and/or wellness recommendationfor an animal. The recommendation (which may be, for example, in theform of a diet, exercise, medication/supplement, treatment protocol,and/or changes in animal owner and/or animal behavior), is preparedbased upon data collected from the animal.

Briefly, therefore, the present disclosure is directed to a method ofpreparing a nutrition, health, and/or wellness recommendation for ananimal. The method comprises collecting the data from the animal,analyzing the data, and providing the nutrition, health, and/or wellnessrecommendation based upon the analyzed data. Preferably, the collecteddata is one or more of a health, diet, behavior, or environmentalparameter of the animal.

The present disclosure is also directed to systems and methods(including computer-implemented systems and methods) of preparing anutrition, health, and/or wellness recommendation for an animal assubstantially described herein.

Other objects and features will be in part apparent and in part pointedout hereafter.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects and advantages of the disclosure willbecome more fully apparent from the following detailed description,appended claims, and accompanying drawings, wherein the drawingsillustrate features in accordance with exemplary aspects of thedisclosure, and wherein:

FIG. 1 illustrates a flowchart depicting exemplary embodiments used inpreparing nutrition, health, and/or wellness recommendations for ananimal in accordance with the present disclosure.

FIG. 2 illustrates exemplary animal sensing and/or monitoring devicesfor use in the systems and methods described herein.

FIG. 3 illustrates a diagram of a mobile system comprising a mobilemodule for permitting a user to communicate remotely with the animalsensing and/or monitoring devices.

FIG. 4 illustrates a computer suitable for implementing an embodiment ofthe monitoring system.

FIG. 5 illustrates a representative block diagram of the elements of thecomputer of FIG. 4 .

FIG. 6 illustrates a sample schematic of a mobile device at which themobile module can be implemented.

FIG. 7 illustrates an exemplary user profile display of the mobilemodule.

FIG. 8 illustrates an exemplary animal profile display of the mobilemodule.

FIGS. 9A-9G illustrate an animal settings display of the mobile module.

FIG. 10 illustrates an exemplary device profile display of the mobilemodule.

FIG. 11 illustrates an exemplary help/support display of the mobilemodule.

FIGS. 12A-12C illustrate exemplary dashboard displays of the mobilemodule.

FIGS. 13A-13E illustrate exemplary data stream displays of the mobilemodule.

FIGS. 14A-14B illustrate exemplary notification displays of the mobilemodule.

FIGS. 15-23 illustrate data collected using exemplary systems andmethods disclosed herein.

For simplicity and clarity of illustration, the drawing figuresillustrate the general manner of construction, and descriptions anddetails of well-known features and techniques may be omitted to avoidunnecessarily obscuring the present disclosure. Additionally, elementsin the drawing figures are not necessarily drawn to scale. For example,the dimensions of some of the elements in the figures may be exaggeratedrelative to other elements to help improve understanding of embodimentsof the present disclosure. The same reference numerals in differentfigures denote the same elements.

The present disclosure has been described herein with reference tovarious exemplary embodiments. However, those skilled in the art willrecognize that changes in modifications can be made to the exemplaryembodiments without departing from the scope of the present disclosure.As used herein, the terms “comprises,” “comprising,” “includes,”“including” and/or any other variation thereof, are intended to cover anon-exclusive inclusion, such that a system, process, method, article,and/or apparatus that comprises a list of elements does not include onlythose elements but can include other elements not expressly listedand/or inherent to such system, process, method, article, and/orapparatus. Further, no element described herein is required for thepractice of the disclosure unless expressly described, e.g., as“essential” and/or “critical.”

It must also be noted that, as used in this specification and theappended claims, the singular forms “a,” “an” and “the” include pluralreferents unless the content clearly dictates otherwise.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which the disclosure pertains. Although a number of methodsand materials similar or equivalent to those described herein can beused in the practice of the present disclosure, certain preferredmaterials and methods are described herein.

The terms “first,” “second,” “third,” “fourth,” and the like in thedescription and in the claims, if any, are used for distinguishingbetween similar elements and not necessarily for describing a particularhierarchical, sequential, or chronological order. It is to be understoodthat the terms so used are interchangeable under appropriatecircumstances such that the embodiments described herein are, forexample, capable of operation in sequences other than those illustratedor otherwise described herein. Furthermore, the terms “comprise,”“include,” and “have,” and any variations thereof, are intended to covera non-exclusive inclusion, such that a process, method, system, article,device, or apparatus that, comprises a list of elements is notnecessarily limited to those elements, but may include other elementsnot expressly listed or inherent to such process, method, system,article, device, or apparatus.

The terms “left,” “right,” “front,” “back,” “top,” “bottom,” “over,”“under,” and the like in the description and in the claims, if any, areused for descriptive purposes and not necessarily for describingpermanent relative positions. It is to be understood that the terms soused are interchangeable under appropriate circumstances such that theembodiments described herein are, for example, capable of operation inother orientations than those illustrated or otherwise described herein.

The terms “couple,” “coupled,” “couples.” “coupling,” and the likeshould be broadly understood and refer to connecting two or moreelements or signals, electrically, mechanically, or otherwise. Two ormore electrical elements may be electrically coupled, but notmechanically or otherwise coupled; two or more mechanical elements maybe mechanically coupled, but not electrically or otherwise coupled; twoor more electrical elements may be mechanically coupled, but notelectrically or otherwise coupled. Coupling (whether mechanical,electrical, or otherwise) may be for any length of time, e.g., permanentor semi-permanent or only for an instant.

“Electrical coupling” and the like should be broadly understood andinclude coupling involving any electrical signal, whether a powersignal, a data signal, and/or other types or combinations of electricalsignals. “Mechanical coupling” and the like should be broadly understoodand include mechanical coupling of all types. The absence of the word“removably,” “removable,” and the like near the word “coupled,” and thelike does not mean that the coupling, etc. in question is or is notremovable.

DETAILED DESCRIPTION

In general, the systems and methods described herein involve thecollection, analysis, and/or use of animal data to providerecommendations to the appropriate individuals (e.g., theowner/caretaker of the animal, veterinary personnel, etc.) on improvingthe overall nutrition, health, and wellness of the animal. As describedherein, this data and its analysis can provide meaningful outcomes,insights, and advice about the animal that enable the individual to takerecommended steps to improve the well-being of the animal. Through avariety of data collection techniques, discussed in detail below,various data regarding the animal can be generated and advice andrecommendations can be communicated to the individual (or a group ofindividuals) to enhance the nutrition, health, and wellness profile ofthe animal.

A general framework of the systems and methods described herein isillustrated in FIG. 1 . As shown, various animal data 2 is combined withexpert analytics 4 to provide the nutrition, health, and/or wellnessrecommendations for the animal. Such data and recommendations can bestored 8 as described herein. Further, personalized user experiences andinformation presentation 10 are provided, e.g., by way of mobile modulesin a mobile device, described below. This may also facilitatecommunication and information sharing 12 with health professionals.These various components are described in detail herein.

The data being acquired can be categorized into a range of data types.For instance, and as discussed in further detail below, the data can beprovided by an individual (e.g., owner, caretaker, or veterinarypersonnel) based upon observation or personal knowledge, or may bederived from sensor or measurement technology placed on or around theanimal or at locations the animal frequents (e.g., collar/leash,feeding/water stations, litter box, etc.); that is, the animal'senvironment. All data that is collected becomes resident in a commondata structure (whether specific for the particular animal or across abroader spectrum of breeds or types of animal).

The data is analyzed using various algorithms, formulas, andcalculations which, in essence, codify fundamental expert knowledge andapplied science and research regarding health, nutrition, and wellnesscharacteristics of animals, as well as predictive analytics, to create asystem that is capable of continuously screening the new data andcomparing it to historically derived data. In this way, important andmeaningful outcomes, insights, and predictions can be identified andcommunicated to the relevant individuals.

It will be understood that various mathematical and algorithmictechniques, such as bivariate, multivariate and trend analysis, may beused in the analysis of the collected data. The combination of raw datacollected over time and processed (derived) data accumulated over timefor each animal can be used to develop a profile of nutrition, health,and/or wellness of the animal. Other examples may involve the use ofvarious mathematical and algorithmic techniques, such as calculation ofa covariance matrix and further application of Kalman filter fortracking the mean and covariance of an evolving process and atypicaldeviations from baselines. Other particular examples include causalconditional-type algorithms (e.g., if X then Y, where X is a cause of Y)and conditional probability-type algorithms (e.g., the probability of anevent A that another event B has occurred). Further trend analysis canbe used to assess whether an atypical variation is random or whether atrend is developing.

As noted, the algorithms are capable of continuously analyzing andassessing the data to produce predictive outcomes or results of the dataanalysis. The outcomes of these algorithmic and predictiveanalytics-based calculations may then be further screened and analyzedthrough expert knowledge and applied science to provide the nutrition,health, and/or wellness recommendations. It will be understood that someoutcomes, and therefore recommendations, will be identified as being ofhigher importance than others. For example, outcomes, insights, andrecommendations can range from irrelevant (and perhaps even unworthy ofrecommendation) to highly significant or critical (and perhaps worthy ofan alert due to a high perceived risk to the animal). Many outcomes,insights, and recommendations will fall between these two extremes toprovide meaningful advice to improve animal nutrition, health, and/orwellness. As will be discussed in further detail below, this may includerecommended dietary changes based on a perceived health risk, suggestedexercise plans based on perceived behavioral issues, and the like.

Outcomes and insights, and therefore recommendations, having little orno relevance may or may not be communicated to the appropriateindividual. Those generating relevance, on the other hand, will bequeued within the system for communication to the appropriate individualwhen/if appropriate. It will be understood that the individual may havethe ability within the system to set threshold boundaries for the typeand level of insights that they deem relevant or not. Outcomes,insights, and recommendations viewed as highly relevant or alert-worthycan be prioritized for immediate notification to the appropriateindividual(s). It is also envisioned that multiple individuals could benotified of high relevance outcomes and recommendations (e.g., theanimal owner/caretaker and the animal's veterinarian). Communications tothe individual(s) may be made via software web-based or applications,e-mail, text, phone, or any other forms of electronic communication. Forless than highly or materially relevant outcomes and recommendations,the individual(s) may receive a report from the system on a daily,weekly monthly, or yearly basis, or other relevant time frame.

Engagement of the individuals with and to the system can also be viaweb-based or software applications, e-mail, text, phone, and otherrelevant forms of electronic communication. This may also includeinteractive websites and social or peer-to-peer media applications andprotocols. In this way, the individual can have the ability to tailorthe user experience and preferences to fit their and the animal's needs.As discussed in further detail below, general categories of, feedbackand/or recommendations include any number of nutrition, health, andwellness aspects of the animal. This may include, for example, generalhealth characteristics and levels of risk; behavior aspects such asmeaningful patterns and training/modification advice, includingrecommended changes in animal owner and/or animal behavior; activityaspects including meaningful patterns and modification advice;nutritional aspects including what and how to feed the animal and othergeneral and specific advice and product recommendations for the animal;alerts and other notifications of any high-risk and/or critical,outcomes and recommendations; and packaging of data and reports for usein conjunction with veterinary visits.

The systems and methods can also be configured to communicate with theappropriate individual, for example, by an alert or other message. Themessage or alert can correspond, for example, to a particular event orsequence of events observed by the collected data, or to the breach of athreshold(s) (either by reaching, exceeding, or falling below athreshold value(s) or condition(s)), whether predetermined or set by theuser, for either collected or analyzed data. A message or alert can thenbe sent when the threshold data has been met. Communications of or aboutthe message or alert may be sent to the individual(s) via softwareweb-based or applications, e-mail, text, phone, or any other forms ofelectronic communication, and typically those with instant or relativelyprompt access by the individual(s) such as phone, text, or e-mail.

It will be understood that any animal (and its owner) can be theintended beneficiary of the systems and methods described herein. Thus,the animal may be a companion animal such as dogs and cats, a farmanimal such as cows, horses, swine, as well as birds and exotic animalsuch as zoo animals. In one particular embodiment, the animal is a dogor a cat. In another particular embodiment, the animal is a dog, a cat,or a multiple or combination thereof.

Animal Data

As discussed above, the outcomes and recommendations for improving orenhancing the nutrition, health, and or wellness of the animal aredetermined using various data 2 collected from the animal (FIG. 1 ).This can involve any one or more characteristics, or parameters,exhibited or possessed by the animal, or otherwise present in connectionwith the animal (such as environmental factors), In a particularembodiment, the foregoing analysis is performed on one or more of ahealth, diet, behavior, and environmental parameter of the animal.

Representative health parameters of the animal may include, for example,age; sex; gender; species or breed; body weight; body mass index (BMI);body composition; body condition score; body temperature; gait force;reproductive aspects (e.g., estrus, spay/neuter status, etc.); skin andcoat condition; UV exposure; cardiovascular system (e.g., heart rate);respiratory system (e.g., respiration rate); gastrointestinal and kidneyfunctions (e.g., fecal composition, urine chemistry, etc.); vision,cognitive health; combinations thereof; and the like.

Representative diet parameters of the animal may include, for example,food and water consumption including amounts and time of day;nutritional composition or profile of the food consumed; vitamin,supplement, and/or medication consumption; combinations thereof; and thelike.

Representative behavior parameters of the animal may include, forexample, activity profiles (e.g., calories burned, steps or distancetraveled, intensity levels, changes in elevation, and time of dayinformation); elimination activity including frequency, amount, and timeof day information; vocalization (e.g., barking, meowing, and othersounds that can indicate animal dispositions); combinations thereof; andthe like.

Representative environmental parameters of the animal may include, forexample, weather information (e.g., air temperature, humidity, heatindex, precipitation, etc.); location coordinates of animal; locationcoordinates of food/water/waste container/sleeping or restinglocations/etc.; presence or absence of owner/caretaker at the location;presence or absence of children/elderly at the location; combinationsthereof; and the like.

Taken as a whole, therefore, exemplary animal data may include, forexample, any observable measure of the health or physical state of ananimal determined by various means, and may be quantitative orqualitative, such as a weight of an animal, a weight of a wastedeposited by an animal in a waste container, a body temperature of ananimal, the weight of a platform before the presence of the animal isdetected, the combined weight of the platform and the animal after thepresence of the animal was detected, the weight of a platform after thedeparture of the animal was detected, the weight of the food consumed bythe animal, the weight of the water consumed by the animal, the datewhen presence of the animal is detected, the time when presence of theanimal is detected, the time when departure of the animal is detected,the duration of time between detection of the presence of the animal andthe departure of the animal, a tip of the nose temperature of an animal,an ear temperature of an animal, an anal temperature of an animal, aheight of an animal, a video or a picture or plurality thereof of ananimal, a video or a picture or plurality thereof of animal body partssuch as a face, an eye, eyes, parts of a skin, a paws, a video or apicture or plurality thereof of a waste container, a video or a pictureor plurality thereof of a waste left by an animal, a video or a pictureor plurality thereof of a substance in a waste container, a voicerecording for the duration of animal's presence inside a wastecontainer, a result of chemical, biological or biochemical analysis, thedaily frequency with which presence of the animal is detected, thecumulative daily weight of the animal's waste, the cumulative dailyweight of the food consumed by the animal, the cumulative daily weightof the water consumed by the animal, the average daily weight of theanimal, the maximum and the minimum daily weight of the animal, thecumulative daily duration of time between each detection of the presenceof the animal and the departure of the animal, the average, maximum andminimum rates of food and water consumption, expressed in weight of foodand water consumed per unit of time, the cumulative daily number oftimes the presence of the animal is detected, the amount of time sincethe last time presence of the animal is detected, or the average dailytime interval between instances where presence of animal is detected,and combinations and variations thereof.

In some embodiments, data on single or multiple parameters may becollected and analyzed. Thus, in one embodiment, the data collection andanalysis may be performed on one of a health parameter, a dietparameter, a behavior parameter, or an environmental parameter. Inanother embodiment, the data collection and analysis may be performed ontwo or more of a health parameter, a diet parameter, a behaviorparameter and an environmental parameter Data collection and analysis ofcombinations of parameters may therefore also be performed.

For example, the data collection and analysis may be performed on healthand diet parameters; heath and behavior parameters; health andenvironmental parameters; diet and behavior parameters; diet andenvironment parameters; behavior and environment parameters; health,diet, and behavior parameters; health, diet, and environmentalparameters; health, behavior, and environment parameters; diet,behavior, and environmental parameters; and health, diet, behavior, andenvironmental parameters.

It will be understood that, for a multi-animal home or dwelling, it willin many respects be advantageous to have the ability to uniquelyidentify each animal and the parameters of the same that are collect andanalyzed. In this way, the systems and methods have the ability touniquely identify individual animals using the same system so that thedata analysis is unique to each animal regardless of identity or evenspecies (e.g., the possibility of having a single system in a home thatcaptures data for both dogs and cats). For example, where multipleanimals use a single waste container, each animal could be identified ordistinguished based upon trends or observations (such as by weight,typical time of day of use, typical length of stay in the container,typical amount of waste deposited, etc.). By way of another example,where multiple animals use a single food and/or water container, eachanimal could be identified or distinguished based upon trends orobservations (such as by weight, typical time of day offeeding/watering, typical length of stay at the food/water container,typical amount of food/water consumed, etc.). By way of further example,multiple measurement devices (e.g., including sensors) can be employedto accommodate multiple animals, such as distinct food/water containers,sleeping/resting locations, etc. In this way, the various systems andmethods described herein can support any combination of single ormultiple animals and single or multiple measurement/sensor devices.

Analysis of one or more of the foregoing parameters using collected datacan thereafter be used to provide predictive outcomes andrecommendations on nutrition, health, and/or wellness of the animal.

By way of example, and not by way of limitation, collected and analyzeddata regarding animal heart rate can be indicative or otherwiseinformative of the animal's stress level; the animal's maximum/minimumheart rate; the animal's eating habits or food palatability; any painexperienced by the animal; the animal's excitement level; number ofcalories burned; comparative analysis of heart rate and activity level;aerobic capacity; joint/mobility issues; sleep/dream tracking; presenceor absence of arrhythmia; post-surgery, post-illness or post-exercisereturn to baseline or normal; incident based anxiety (e.g., presence ofthe mailman or garbage truck); visitor/stranger acceptance; combinationsthereof; and the like. These collected data and analysis may, in turn,lead to outcomes and recommendations regarding one or more of changes inenvironment; initiating, limiting, or increasing exercise protocols;administration or cessation of vitamins, supplements, or medication;initiating or modifying training protocols; nutritional/feeding changes;veterinary visits; combinations thereof; and the like.

By way of another example, and not by way of limitation, collected andanalyzed data regarding food consumption of the animal (including amountand time-of-day patterns), can be indicative or otherwise informative ofthe animal's enjoyment or liking of the food; whether one animal iseating another animal's food (i.e., in a multi-animal house ordwelling); normal or irregular food ingestion rates (e.g., too fast ortoo slow); illnesses or gastrointestinal issues; seasonality issues(e.g., changes in patterns based on changes in temperature); nutrientdeficiencies based on amount of food consumed; over/under feedingissues; hyper/hypophagia; combinations thereof; and the like. Thesecollected data and analysis may, in turn, lead to outcomes andrecommendations regarding one or more of changes in environment;initiating, limiting, or increasing exercise protocols; administrationor cessation of vitamins, supplements, or medication; initiating ormodifying training protocols; nutritional/feeding changes; veterinaryvisits; combinations thereof; and the like.

By way of another example, and not by way of limitation, collected andanalyzed data regarding active minutes per day of the animal and thetiming thereof can be indicative or otherwise informative of theanimal's Circadian rhythms; aging; general health and fitness; metabolicdisease; illness or malaise; anxious times or periods during the day;dementia or cognitive issues; joint or mobility issues; changes in lifestage (puppy/adult/senior); effectiveness of recovery fromillness/injury/surgery; effectiveness of diet and nutrition; multipleanimal household relationships; combinations thereof; and the like.These collected data and analysis may, in turn, lead to outcomes andrecommendations regarding one or more of changes in environment;initiating, limiting, or increasing exercise protocols; administrationor cessation of vitamins, supplements, or medication; initiating ormodifying training protocols; nutritional/feeding changes; veterinaryvisits; combinations thereof; and the like.

By way of another example, and not by way of limitation, collected andanalyzed data regarding number of steps taken per day by the animal canbe indicative or otherwise informative of the time of day when calorieburn is elevated or decreased; the social ability of the animal; thetotal motion of the animal; anxiety level of the animal (e.g., pacingwhile the owner/caretaker is away); speed and changes in speed over timethat can indicate stiffness or joint/mobility issues; dementia andcognitive health; illness or injury in limbs; incident based anxiety(e.g., presence of the mailman or garbage truck); Circadian rhythms;waking/sleeping schedules; post-surgery, post-illness, or post-exercisereturn to baseline or normal; rate of aging or relative age of animal,basal metabolism; need for more physical activity; need for increased ordecreased activity or exercise; combinations thereof; and the like.These collected data and analysis may, in turn, lead to outcomes andrecommendations regarding one or more of changes in environment;initiating, limiting, or increasing exercise protocols; administrationor cessation of vitamins, supplements, or medication; initiating ormodifying training protocols; nutritional/feeding changes; veterinaryvisits; combinations thereof; and the like.

By way of another example, and not by way of limitation, collected andanalyzed data regarding the number of calories burned per day by theanimal can be indicative or otherwise informative of the animal'smetabolism; the calories required by the animal and the amount offood/treats to provide; particular type of food/treats to give theanimal (e.g., performance or weight management); feed/treating times ofday; activity when owner/caretaker is away; joint/mobility issues;energy expenditure; dementia or cognitive issues; increased water needs;combinations thereof; and the like. These collected data and analysismay, in turn, lead to outcomes and recommendations regarding one or moreof changes in environment; initiating, limiting, or increasing exerciseprotocols; administration or cessation of vitamins, supplements, ormedication; initiating or modifying training protocols;nutritional/feeding changes; veterinary visits; combinations thereof;and the like.

By way of another example, and not by way of limitation, collected andanalyzed data regarding the body weight of the animal can be indicativeor otherwise informative of changes over time (e.g., over/under weight,over/under feeding; protein levels; by-breed comparisons; onset ofillness; gastrointestinal issues; diseases, conditions, or other healthissues (e.g., thyroid problems, tumors, etc.); energy balance; need tochange foods based on life stage (e.g., when weight plateaus in puppies,begins declining in older dogs, etc.); effectiveness of weight loss/gainprograms or diets; daily caloric needs; resting metabolism; water/foodintake; combinations thereof; and the like. These collected data andanalysis may, in turn, lead to outcomes and recommendations regardingone or more of changes in environment; initiating, limiting, orincreasing exercise protocols; administration or cessation of vitamins,supplements, or medication; initiating or modifying training protocols;nutritional/feeding changes; veterinary visits; combinations thereof;and the like.

By way of another example, and not by way of limitation, collected andanalyzed data regarding water consumption of the animal can beindicative or otherwise informative of animal hydration levels/status(e.g., as compared to body weight to determine if hydration levels areadequate); dehydration/salt content; diabetes or the onset thereof; theanimal's meeting of hydration requirements; fluctuations in waterconsumption; the water's use as a media for delivery of supplements ormedication; elimination behaviors; anxiety, stress, or boredom; risks ofrenal crystals; when water source/container needs replenished;seasonality; risks of renal failure; drinking frequency and changes overtime; time-of-day patterns; cleanliness of water source/container; foodconsumption and type; potential consumption of inappropriate food/items;combinations thereof; and the like. These collected data and analysismay, in turn, lead to outcomes and recommendations regarding one or moreof changes in environment; initiating, limiting, or increasing exerciseprotocols; administration or cessation of vitamins, supplements, ormedication; initiating or modifying training protocols;nutritional/feeding changes; veterinary visits; combinations thereof;and the like.

In addition, collected data and analysis on certain parameters can beindicative of a number of particular issues for the animal. For example,one or more changes in animal activity; changes in restperiods/intensity; changes in food/water consumption; changes in stepstaken; changes in weight; irregular elimination behavior; bodytemperature; results of blood, urine, and/or stress tests; andcombinations thereof, may be indicative or otherwise informative ofcertain cancers in the animal. By way of another example, changes infood/water consumption; changes in weight; seasonality; abnormalscratching; hair loss; changes in appearance; and combinations thereof,may be indicative or otherwise informative of allergies in the animal(whether food allergies, environmental allergies, or bacterial/viralallergies). By way of another example, changes in activity; number ofsteps (e.g., pacing); heart rate; increased water intake and decreasedfood intake; vocalization (e.g., whining); and combinations thereof, maybe indicative or otherwise informative of anxiety, stress, or boredom inthe animal. By way of another example, the age; breed; reproductiveaspects (e.g., estrus, spay/neuter status, etc.); rest patterns;activity patterns including number of steps and calories burned; changesin caloric intake; changes in feeding patterns; and combinationsthereof, may be indicative of the life stage (or a change thereof) ofthe animal. By way of another example, increases in water intake;increases or decreases in body weight; the age and breed of the animal;urine color; decreases in activity; food type; and combinations thereof,may be indicative of diabetes in the animal. These collected data andanalysis may, in turn, lead to outcomes and recommendations regardingone or more of changes in environment; initiating, limiting, orincreasing exercise protocols; administration or cessation of vitamins,supplements, or medication; initiating or modifying training protocols;nutritional/feeding changes; veterinary visits; combinations thereof;and the like.

Differing combinations of collected data and analysis on certainparameters can also be indicative of multiple issues for the animal. Byway of example, the combination of heart rate and body weight data, maybe indicative or otherwise be informative of hypertension; anorexia;hyperfusia; fitness; exertion; anxiety, stress, or boredom of theanimal. By way of another example, the combination of heart rate, bodyweight, and body composition data may be indicative or otherwiseinformative of aging; obesity; training deficiencies; fitness issues;metabolic needs; and nutritional needs of the animal. By way of anotherexample, the combination of heart rate, body weight, and vocalizationdata can be indicative or otherwise informative of anxiety, stress, orboredom, or physical or emotional distress of the animal. By way ofanother example, the combination of weight, body temperature, heartrate, and respiration data can be indicative or otherwise informative ofthe overall health and well-being of the animal. By way of anotherexample, increased water intake of the animal can be indicative orotherwise informative of anxiety, stress, or boredom; urinary tractissues; increased calcium levels; liver disease; hyperthyroidism; andacute and chronic renal issues of the animal. By way of another example,the number of calories burned per day; resting minutes per day; stepstaken per day; and location of the animal can be indicative or otherwiseinformative of weight and diet issues; metabolic issues; activitypatterns; pre-disease status; baseline and adjusted fitness and activitylevels; multi-animal household issues of the animal; dementia andcognitive issues; and the general well-being of the animal. By way ofanother example, food intake, water intake, body weight and activitylevels can be indicative or otherwise informative of body massindications; elimination behavior; palatability of food; food/watercontainer issues; weight gain/loss (e.g., due to Addison's disease,hypothyroidism); early disease state or onset; advanced disease states;stress patterns; renal issues; arthritis; joint/mobility issues;training deficiencies; aging; and life stage changes of the animal. Byway of another example, food intake, water intake, number of stepstaken, body weight. and heart rate can be indicative or otherwiseinformative of energy balance (e.g., by breed and/or by life stage);baseline and adjusted happiness/contentment/satisfaction levels; changesin energy levels; disease status; food suitability and palatability; andanxiety, stress, or boredom of the animal. By way of another example,food intake, water intake, activity level. body weight, age, heart rate,and body temperature can be indicative or otherwise informative ofnutrition/malnutrition issues; cancers; renal issues; hyperthyroidism;and infectious diseases of the animal. By way of another example, bodyweight, age, breed, activity levels, glucose levels, and water intakecan be indicative or otherwise informative of diabetes or onset thereof,and musculoskeletal diseases such as hip dysplasia and osteoarthritis.These collected data and analysis may, in turn, lead to outcomes andrecommendations regarding one or more of changes in environment;initiating, limiting, or increasing exercise protocols; administrationor cessation of vitamins, supplements, or medication; initiating ormodifying training protocols; nutritional/feeding changes; veterinaryvisits; combinations thereof; and the like.

Still further examples of relevant data and analysis include one or moreof the following: the combination of heart rate and respiration rate ofthe animal; urine chemistry as an indicator of physiological changeswithin the animal over time; body condition scoring, e.g., wherebyanimal owners rate the body condition of the animal (including, forexample, providing photographs of the animal when creating animalprofiles in the mobile modules discussed below); nutritionalcomposition/profile of the animal's food (including, for example,providing photographs of the bar codes or other information on the foodthey feed their animals, such that databases can be accessed to providethe label declaration nutrition analysis on such products) which canprovide insights into the animal's consumed nutrition levels (e.g., forcomparing different manufacturer's products, batch analysis, etc. todetermine true caloric intake and nutrition composition levels in theanimal); UV exposure and related diseases; elevation (e.g., goingup/down steps, climbing hills, etc.) and normal rate ofstanding/sitting/laying changes over time as a predictor of early onsetof joint health problems; animal body temperature versus ambienttemperature around the animal. Still other examples of data includelinking to weather sites, correlating behavior of individual andmultiple pets to earthquake monitoring data, using facial recognition asa way to identify which animal is using a device (who iseating/drinking, using the scale, using the litter box, etc.), GPS orother location-monitoring technologies to pinpoint location of theanimal (e.g., in/out of house, etc.).

Expert Analytics

In addition to the animal data 2, the systems and methods disclosedherein utilize expert analytics 4 to provide more accurate and/ormeaningful recommendations regarding animal health and/or wellness. Thetechniques of the present disclosure thus provide the capability toextract informative data from the raw data, which is then collected andanalyzed by relevant human expert analysis. As depicted in FIG. 1 , forexample, among the various experts are veterinarians, physiologists,geneticists, trainers, behaviorists, nutritionists, and data scientists.

Expert review in real-time or over an extended period of time is used todetermine the optimum therapeutic/nutritional index or recommendationfor that particular animal or animal class. For example, if a thresholdlevel or baseline of the collected data discussed above is breached,appropriate action can be recommended by the expert and taken by theanimal owner or other individual. An appropriate action could bealerting the owner/individual, stopping or starting certain medicationor the like. As will be understood, the appropriate action orrecommendation for an animal would be decided based on the collecteddata and the expert's experience and judgment for that particular animalor class of animals. In will also be understood that the expert analysiscan occur as a one-time exercise using the data set derived from theanimal, and/or as an ongoing exercise using clinical studies and/orexisting clinical information, for instance.

Thus, the expert has the ability to draw upon his or her own experience,and also has access to additional information, e.g., historicalinformation within the system memory, historical information about theparticular animal from one or more accessible databases, and informationabout a plurality of animals from still other databases. The expert(s)may have a variety of control-sharing relationships with the systems andmethods described herein from complete control to provide insight orrecommendations, or a sharing arrangement in which, for example,multiple experts are able to provide insight and recommendations inorder to influence treatment or actions taken by the user/animal owner.Further, the experts are able in some embodiments to prepare and sendanalytics-generated messages (e.g., pet health and wellness information)and system information messages within the system (e.g., via the mobilemodule discussed in detail below).

Animal Data Collection

The aforementioned animal health, behavior, and/or environmental datacan be collected or derived and analyzed using a number of techniquesand/or sensing/monitoring devices.

The data may be derived from qualitative observations by animalowners/caretakers or periodic veterinary examinations. This may includeobserved and recorded changes in weight, activity, food and/or waterconsumption, elimination frequency and consistency, and the like, ascompared to prior observations and recordation of the same.Additionally, or alternatively, the data can be collected on anautomated basis, either continuously or and periodic intervals, usingone or more sensors associated with, for example, the animal itself orlocations frequented by the animal (e.g., food/water containers, wastecontainers, frequent sleeping/resting locations, etc.) and measuringdevices.

For example, data can be continuously captured during the entireduration of the animal's activity inside a waste container, during foodor water consumption, sleep or rest until the animal moves awayeffectively disengaging measurement. Data can also be captured byperiodically sampling a sensor or sensors, such as weight, pressure orforce sensor or sensors (such as strain gauges, load cells, piezosensors, etc.) and converting a contiguous (analog) electrical signalinto a digital data.

Thus, a variety of sensors and measuring devices may be utilized in thedata collection step. Exemplary sensors include, but are not limited to,accelerometers (single axis or multi-axis), gyroscopes, weighing scales,weight transducers, force transducers, displacement transducers,orientation sensors (e.g., compasses), pressure transducers, weightsensors, force sensors, pedometers, displacement sensors, pressuresensors, load cells, photographic cameras, video cameras, camcorders, RFlocation beacons, contact thermometers, non-contact thermometers, suchas infrared thermometers, laser thermometers, infrared pyrometers, laserpyrometers, litters or litter additives that change their properties,such as color, odor, outgassing, fluorescence, luminescence, when comein contact with animal waste, either urine or excrements. Other sensorsmay also be used to determine an animal's presence or absence at aparticular location or height, such as optical sensors, opticalreflecting sensors, LED/photodiode pair optical sensors,LED/phototransistor pair optical sensors, laser diode/photodiode pairoptical sensors, laser diode/phototransistor pair optical sensors,optocouplers, optical fiber coupled optical sensors, magnetic sensors,weight sensors, force sensors, displacement sensors, pressure sensors(relative/differential or absolute), various proximity sensors, such asinductive proximity sensors, magnetic proximity sensors, capacitiveproximity sensors, global positioning system (GPS) devices, a globalnavigation satellite system (GNSS) devices, and/or a combinationthereof. In general, all types of sensors and sensing techniques,whether now known or later developed, that are capable of generatingdata which is representative of motion and/or presence of an animal areintended to fall within the scope of the present disclosure.

Particular sensor and measuring devices and methods and systems forusing the same in the collection of physiological and behavioral animaldata, and the storage and transmittal of the same, are described in U.S.Pub. Nos. 2011/0315084; 2012/0299731; 2013/0073254; and 2013/0192526(each of which are hereby incorporated by reference in their entirety).

For example, U.S. Pub. No. 2011/0315084 provides a cat litter boxincluding monitoring system that detects a cat's behavior relative tothe cat litter box. The litter box includes an identification system,such as a radio-frequency identification (RFID) system, in order totrack individual cat activity. As part of the monitoring, data withimportant health implications, such as average trips to the litter boxper a set period of time can be stored and transmitted. User alerts maybe sent if there is a significant change in behavior, such as no visitsto the litter box in a set period of time (e.g., 24 hours). Themonitoring system may also include a weight sensor, such that the litterbox store and transmit historical weight information on the cat(s) thatuse it. User alerts can be sent if a weight change violates a range. Theweight sensor can also be used for the identification of individual catsand/or for the determination of the type and quantity of waste left by acat in the litter box. Health data can be generated as an alert topotential underlying health problems, such as kidney disease ordiabetes, historical weight information as an early indicator of anunderlying disease, or lack of litter box activity which could indicateisolation from the litter box (e.g., locked in a separate area of ahome, sick and/or injured, etc.).

By way of another example, U.S. Pub. No. 2012/0299731 provides a wastecontainer or perch (e.g., for avian animals) comprising a scale andother sensors to measure and/or determine characteristics of the animalwhile it is disposed in the container or on the perch. Feeding and waterstations comprising scales and other sensors for measuring and/ordetermining characteristics of the animal are also disclosed.

By way of another example, U.S. Pub. No. 2013/0073254 provides portablemonitoring devices capable of monitoring, calculating, determiningand/or detecting energy and/or calorie “burn” due to physical activity.The portable monitoring device is affixed to the user during operation,and the housing of the device is of a physical size and shape thatfacilitates coupling to the user via a mechanism (for example, a clip,strap and/or tie) that facilitates coupling or affixing the device tothe user and allows the user to perform normal or typical useractivities without hindering the user from performing such activities.

By way of another example, U.S. Pub. No. 2013/0192526 provides a roverunit (i.e., a pet collar, harness, or clothing) carried by the animalcapable of detecting and transmitting physiological conditions andactions of the animal.

Certain exemplary embodiments of sensing/measuring devices 60 aredepicted in FIG. 2 . For instance, the device 60 may comprise anon-animal monitor 60 a, which may be coupled to the collar, leash, orother accessory of the animal. On-animal devices of this type may beconfigured to measure, among other things, animal surroundings, animalactivity, body temperature, ambient temperature, elevation/altitudechanges, UV exposure, and the like. Another type of device 60 comprisesa nutrition/hydration station 60 b, which may include one or more foodand water receptacles. Devices of this type may be configured tomonitor, among other things, food and water mass consumption,feeding/drinking event duration, eating behavior patterns, and the like.Another type of device 60 comprises a weight monitor 60 c. Devices ofthis type can be placed under the animal's kennel or sleeping/restinglocation, for example, to provide real-time weight tracking. Anothertype of device 60 comprises a litter box activity monitor 60 d, whichmay be positioned on or near the animal's waste container. Devices ofthis type can be configured to monitor, among other things, activityfrequency and duration of use of the waste container. Combinations ofdevices 60 a, 60 b, 60 c, and/or 60 d may be used to provide morecomplete packages of animal data 2. As will be understood, theseexemplary devices can therefore be equipped one or more of the varioussensors discussed above.

Analytical Techniques and Systems

With respect to data analysis, this may include the many types ofsoftware development methodologies and tools/program languages thatexist, such as cloud-based data architectures, “Big Data” analyticssystems and methods (e.g., via Amazon's Elastic MapReduce (EMR) and/orGoogle's I/O), and HTML based applications (e.g., HTML5). Thesemethodologies, tools, and programs may be executed alone or, morepreferably, in conjunction with one or more of (1) inventor's andapplicant's expert knowledge in animal nutrition, health, and wellness;(2) expert knowledge of other individuals and groups in practice andacademia; (3) expert knowledge of data scientists and research anddevelopment individuals and groups to create additional, or alternative,predictive analytics algorithms based on the treatment of the datacollected on individual animals (i.e., data scientists associated withthe applicant, as well as, other third party groups and partners); and(4) emerging machine-learning technologies that are capable ofautomating data analysis using high-speed processors to identifysignificant trend and insights within the data set.

As those skilled in the art will appreciate, the various systemcomputing components discussed herein can include one and/or more of thefollowing: a host server and/or other computing systems including aprocessor for processing digital data; storage or memory coupled to saidprocessor for storing digital data; an input digitizer coupled to theprocessor for inputting digital data; an application program stored insaid memory and accessible by said processor for directing processing ofdigital data by said processor; a display device coupled to theprocessor and memory for displaying information derived from digitaldata processed by said processor; and a plurality of databases. Thecomputing systems can include an operating system (e.g., OS/360, MVS,Windows NT, 95/98/2000/XP/Vista, OS2, UNIX, Unix-like, TPF, Linux,Solaris, MacOS, Mac OS X, AIX, Google Chrome OS, Plan 9, Android, iOS,Blackberry, Windows Phone, etc., and the like) as well as variousconventional support software and drivers typically associated withcomputers and mobile/smart phone devices.

As noted above, systems for use in connection with the methods describedherein can include storage devices for storing the collected and/oranalyzed data. Such storage devices may include, for example, memorydevices, data storage devices and a combination thereof such as memorychips, semiconductor memories, Integrated Circuits (IC's), non-volatilememories or storage device such as flash memories, Read Only Memories(ROMs), Erasable Read Only Memories (EROMs), Electrically Erasable ReadOnly Memories (EEROMs), Erasable Programmable Read Only Memories(EPROMs), Electrically Erasable Programmable Read Only Memories(EEPROMs), an Electrically Erasable Programmable Read Only Memory(EEPRO), volatile memories such as Random Access Memories (RAMs), StaticRandom Access Memories (SRAMs), Dynamic Random Access Memories (DRAMs),Single Data Rate memories (SDRs), Dual Data Rata memories (DDRs), QuadData Rate memories (QDR's), microprocessor registers, microcontrollerregisters, CPU registers, controller registers, magnetic storage devicessuch as magnetic disks, magnetic hard disks, magnetic tapes, opticalmemory devices such as optical disks, compact disks (CDs), DigitalVersatile Disks (DVDs), Blu-ray Disks, Magneto Optical Disks (MO Disks),USB flash memory or other external memory devices (e.g., portable harddrives), and/or a combination thereof.

Systems may also include a processor configured to analyze collecteddata. Exemplary processors include, for example, electronic circuits,systems, modules, subsystems, sub modules, devices and combinationsthereof, such as Central Processing Units (CPUs), microprocessors,microcontrollers, processing units, control units, tangible media forrecording and/or a combinations thereof. It will be understood that thesensors and measuring devices, storage devices, and processors may beassembled as a single unit, or as multiple, standalone devices capableof communication with one another.

It will also be appreciated that the present disclosure can be embodiedas a method, a system (e.g., a data processing system), a device fordata processing, a computer program product, and/or a communicationsdevice. Accordingly, the present disclosure can take the form of anentirely software embodiment, an entirely hardware embodiment, and/or anembodiment combining aspects of both software and hardware. Furthermore,the present disclosure can take the form of a computer program producton a computer-readable storage medium having computer-readable programcode means embodied in the storage medium. Any suitablecomputer-readable storage medium can be utilized, including hard disks,CD-ROM, optical storage devices, magnetic storage devices, and/or thelike.

Mobile Monitoring Systems

Turning again to the drawings, FIG. 3 illustrates a diagram of mobileanimal monitoring system 1000, comprising mobile module 2000 forpermitting user 3000 to receive information regarding an animal 40 inits environment 20. As shown, the animal environment includes one ormore sensor/measuring devices 60 as described herein. In the presentembodiment, mobile module 2000 is implemented via mobile device 4000,which is associated with user 3000 and can be, for instance a portableor handheld electronic device such as a cellular phone, a smartphone, apersonal digital assistant (PDA), and/or a tablet device. For instancemobile device 400 can be an electrical device manufactured by Researchin Motion Limited (e.g., a Blackberry® device), Palm, Inc. (e.g., aPalm® device), Apple Computer, Inc. (e.g., an iPod® MP3 player, an iPodTouch® device, an iPad® device, and/or an iPhone® device), and/orSamsung Electronics Co. Ltd. (e.g., a Galaxy® device). In otherexamples, mobile device 400 can be a portable computer (e.g., a laptopor similar device such as those manufactured by the aforementioned, orother, companies).

Mobile device 4000 can be configured to establish a wireless connection6100 with Internet 6000. Similarly, the animal data collection device(s)60 can be configured to communicate via Internet 6000 through connection6200, which may be wired or wireless. Thus, mobile device 400 and datacollection device 60 can communicate via Internet 6000. In someexamples, a portion of connection 6100 and/or of connection 6200 can becarried out via a network configured for a wireless and/or cellularstandard such as WiFi (IEEE 802.11a/b/g/n), WiPAN (IEEE 802.15,Bluetooth®), W-CDMA (Wideband Code Division Multiple Access), HSPA (HighSpeed Packet Access), EDGE (Enhanced Data Rate for GSM Evolution), WiMAX(Worldwide Interoperability for Microwave Access), LTE (Long TermEvolution), etc.

FIG. 4 illustrates a computer 7000 suitable for implementing anembodiment of mobile monitoring system 1000. Computer 7000 includes achassis 7020 containing one or more circuit boards (not shown), a USB(universal serial bus) port 7120, a Compact Disc Read-Only Memory(CD-ROM) and/or Digital Video Disc (DVD) drive 7160, and a hard drive7140. A representative block diagram of the elements included on thecircuit boards inside chassis 7020 is shown in FIG. 5 . A centralprocessing unit (CPU) 8100 is coupled to a system bus 8140 in FIG. 5 .In various embodiments, the architecture of CPU 8100 can be compliantwith any of a variety of commercially distributed architecture families.

System bus 8120 also is coupled to memory 8080 that includes both readonly memory (ROM) and random access memory (RAM). Non-volatile portionsof memory 8080 or the ROM can be encoded with a boot, code sequencesuitable for restoring computer 7000 (FIG. 4 ) to a functional stateafter a system reset. In addition, memory 8080 can include microcodesuch as a Basic Input-Output System (BIOS). In the depicted embodimentof FIG. 5 , various I/O devices such as a disk controller 8040, agraphics adapter 8180, a video controller 8020, a keyboard adapter 8200,a mouse adapter 8060, a network adapter 8140, and other I/O devices 8160can be coupled to system bus 8120. Keyboard adapter 8200 and mouseadapter 8060 are coupled in the present example to keyboard 7040 andmouse 7100, respectively, of computer 7000. While graphics adapter 8180and video controller 8020 are indicated as distinct units in FIG. 5 ,video controller 8020 can be integrated into graphics adapter 818, orvice versa in other embodiments. Video controller 8020 is suitable forrefreshing monitor 7090 to display images on a screen 7080 of computer7000. Disk controller 8040 can control hard drive 7140, USB port 7120,and/or CD-ROM or DVD drive 7160. In other embodiments, distinct unitscan be used to control each of these devices separately.

Network adapters 8200 can be coupled to one or more antennas. In someembodiments, network adapter 8200 can be configured for WiFicommunication (IEEE 802.11), and/or may be part of a WNIC (wirelessnetwork interface controller) card (not shown) plugged or coupled to anexpansion port (not shown) in computer 7000. Such WNIC card can be awireless network card built into internal computer 7000 in someexamples. A wireless network adapter can be built into internal clientcomputer 7000 by having wireless Ethernet capabilities integrated intothe motherboard chipset, or implemented via a dedicated wirelessEthernet chip, connected through the PCI (peripheral componentinterconnector) or a PCI express bus. In the same or other embodiments,network adapters 8200 can be configured for communication via otherwireless protocols, such as via WPAN, W-CDMA, HSPA, EDGE, WIMAX, LTE, orothers. In other embodiments, network adapter 820 can be a wired networkadapter.

Although other components of computer 7000 are not shown, suchcomponents and their interconnection are well known to those of ordinaryskill in the art. Accordingly, further details concerning theconstruction and composition of computer 7000 and the circuit boardsinside chassis 7020 need not be discussed herein.

When computer 700 is in operation, program instructions stored on harddrive 714, on memory 808, on a USB drive in USB port 712, and/or on aCD-ROM or DVD in CD-ROM and/or DVD drive 916, can be executed by CPU1010 (FIG. 5 ). Such program instructions may correspond to an operatingsystem (OS) such as an Apple OS, a Microsoft Windows OS, a Linux OS,and/or a UNIX OS, among others. A portion of such program instructionscan be suitable for implementing or carrying out the systems and methodsdescribed herein.

In the present example of FIG. 3 , one or more sensing/measurementdevices 60 are coupled to computer 7000. Alternatively, the devices 60may be coupled to the Internet 6000 (not shown) and the mobile module2000, in which case the computer 7000 is not necessary. Mobile module2000 can be configured to communicate with computer 7000 (or device(s)60) to permit user 3000 to access information collected by the device60.

FIG. 6 illustrates a sample schematic of mobile device 4000. Mobiledevice 4000 comprises processor module 4020 and memory module 4040coupled together to run mobile device 4000. Memory module 4040 cancomprise an operating system which can be accessed therefrom forexecution by processor module 4020 to operate different functions ofmobile device 4000. In some examples, the operating system can comprisean operating system like an iOS® OS from Apple Computer Inc., anAndroid® OS from Google, Inc., and/or a Windows Phone OS, fromMicrosoft, Inc., among others. Mobile device 4000 also comprises displaymodule 4060 coupled to processor module 4020 and configured to presentone or more user interfaces for the operation of mobile device 4000.Processor module 4020 is also coupled to communications module 4080,which can be configured to establish connection 6100 (FIG. 3 ) via oneor more of the wireless standards described above.

Mobile module 2000 is also shown in FIG. 6 as implemented in mobiledevice 4000, and can be coupled to or accessed by processor module 4020and/or display module 4060. Although shown separate from memory module4040 in FIG. 6 , mobile module 2000 can be coupled to and/or stored atmemory module 4040 in some embodiments. For instance, mobile module 2000can comprise a mobile application (mobile app) which may be downloadedvia Internet 6000 from a website or an online application store, and/orwhich may be stored at mobile device 4000.

As shown in FIG. 3 , mobile module 2000 can be configured to provideuser 3000 with access to animal sensing/monitoring devices 60 in theanimal environment 20 via Internet 6000 through connection 6100 betweenmobile device 4000 and Internet 6000 and through connection 6200 betweenInternet 6000 and animal environment 20. Mobile module 2000 can thusallow user 3000 to engage in remote monitoring of the animal 40. Suchmonitoring can comprise, for example, the review of animal activity andbehavior, including food/water consumption, periods of resting and/oractivity, and elimination schedules and routines, among others.

As seen in FIG. 6 , mobile module 2000 can comprise several sub-modules,such as settings module 2020, dashboard module 2040, analytics module2060, and notifications module 2080. An optional login module (notshown) may also be included. If present, the login module can beconfigured to receive authentication information from a user, like user3000 (FIG. 3 ) or an animal health professional, to confirm the user'sidentity prior to providing access to the sub-modules. As isconventional, the authentication information can comprise a usernameand/or a password or personal identification number (PIN) in someexamples.

Settings module 2020 comprises the various user accounts or profiles,animal profiles, mobile device profiles, and help/support functions. Theuser has the ability to create and edit these profiles to include theirpersonal and animal information. FIG. 7 illustrates an exemplaryembodiment of a display 9002 comprising user settings including name90021, communication information (e.g., e-mail) 90022, and a photo 90023of the user. FIG. 8 illustrates and exemplary embodiment of a display9004 comprising user settings including one or more animal profiles90041 being monitored by device(s) 60. These profiles 90041 are createdby providing various details 90061 about the animal, as illustrated indisplays 9006 a-9006 g of FIGS. 9A-9G.

Also in, settings module 2020 is the ability to add device profiles forthe various sensing/measuring devices 60, as shown in exemplary display9008 (FIG. 10 ). This may include, for example, collar 90081, feedingstation 90082, litter box 90083, and/or scale 90084 embodiments such asthose discussed above. The settings module may also include help and/orsupport functionality 90101, as shown in display 9010 (FIG. 11 ).

Turning now to the dashboard module 2040, this module comprisesanalytics-generated messages (e.g., pet health and wellness information)and system information messages (e.g., device power, connectivity,etc.). FIGS. 12A-12C illustrate exemplary embodiments of displays 9012a-9012 c. Here, activity information regarding the animal, as detectedby the various devices 60, are conveyed to the user via the mobiledevice 4000. As shown, the activity information may includeeating/drinking activity 90121, litter box/elimination activity 90122,and/or physical activity/resting details 90123.

Next, the analytics module 2060 comprises individual data stream detailsby data type and animal, as collected by device(s) 60. FIGS. 13A-13Eillustrate exemplary embodiments of displays 9014 a-9014 e showing suchdata stream details as activity 90141, rest 90142, food consumption90143, water consumption 90144, and weight 90145 for a selected animal90146. These details may be provided and displayed in variety of ways,including, for example, the depicted graphs charting day, time, amount,etc., or by way of other charts/graphs and/or illustrations. The usercan have the ability to tailor the displays to his or her liking, e.g.,via the settings module. The analytics module may also be configured togenerate and present reports 20610, 20620 including the data streamdetails, which can, in turn, be printed, saved, and/or shared as part ofan animal “journal” or “log” discussed below.

Turning now to the notifications module 2080, this module comprisesadditional analytics and system information messages. For example, FIG.14A illustrates and exemplary embodiment of a display 9016 a showingdetails 90161 regarding if/when a selected animal 90162 has interactedwith one or more of the sensing/measurement devices 60. Notificationsmodule 2080 may also include “journal”- or “log”-type functionality, inwhich captured behaviors or activities (such as eating or drinking, asillustrated in exemplary display 9016 b (FIG. 14B) are logged orrecorded in the module. Here, such relevant or potentially relevantinformation, including user tagged messages 90163, can be collected andsaved for sharing, e.g., with the veterinarian or health care providerof the selected animal 90162. In addition, and similar to the analyticsmodule 2060, the notifications module may also be configured to generateand present reports 20810, 20820 including analytics and systeminformation details, which, in turn, can be printed, saved, and/orshared as part of the animal's “journal” or “log.”

In some instances, the exemplary modules described above may beimplemented as machine-accessible instructions utilizing any of manydifferent programming codes stored on any combination ofmachine-accessible media embodied in a mobile application (e.g., an app)and/or an online application for various wired and/or wireless mobilecommunication devices such as handheld computers, smartphones, portablemedia players, tablet computers, etc. In addition or alternatively, themachine-accessible instructions may be embodied in a volatile ornon-volatile memory or other mass storage device (e.g., a USB drive, aCD, or a DVD). For example, the machine-accessible instructions may beembodied in a machine-accessible medium such as a programmable gatearray, an application specific integrated circuit (ASIC), an erasableprogrammable read only memory (EPROM), a read only memory (ROM), arandom access memory (RAM), a flash memory, a magnetic media, an opticalmedia, and/or any other suitable type of medium. The systems, apparatus,methods, and articles of manufacture described herein are not limited inthis regard.

It should be understood that various changes and modifications to thepresently preferred embodiments described herein will be apparent tothose skilled in the art. Such changes and modifications can be madewithout departing from the spirit and scope of the present invention andwithout diminishing its intended advantages. It is therefore intendedthat such changes and modifications be covered by the appended claims.

All elements claimed in any particular claim are essential to theembodiment claimed in that particular claim. Consequently, replacementof one or more claimed elements constitutes reconstruction and notrepair. Additionally, benefits, other advantages, and solutions toproblems have been described with regard to specific embodiments. Thebenefits, advantages, solutions to problems, and any element or elementsthat may cause any benefit, advantage, or solution to occur or becomemore pronounced, however, are not to be construed as critical, required,or essential features or elements of any or all of the claims, unlesssuch benefits, advantages, solutions, or elements are expressly statedin such claims.

Moreover, embodiments and limitations disclosed herein are not dedicatedto the public under the doctrine of dedication if the embodiments and/orlimitations: (1) are not expressly claimed in the claims; and (2) are orare potentially equivalents of express elements and/or limitations inthe claims under the doctrine of equivalents.

Having described the invention in detail, it will be apparent thatmodifications and variations are possible without departing the scope ofthe invention defined in the appended claims. Furthermore, it should beappreciated that all examples in the present disclosure are provided asnon-limiting examples.

EXAMPLES

The following non-limiting examples are provided to further illustratethe present invention. It should be appreciated by those of skill in theart that the techniques disclosed in the examples that follow representapproaches the inventors have found function well in the practice of theinvention, and thus can be considered to constitute examples of modesfor its practice. However, those of skill in the art should, in light ofthe present disclosure, appreciate that many changes can be made in thespecific embodiments that are disclosed and still obtain a like orsimilar result without departing from the spirit and scope of theinvention.

Example 1—Unexpected Dog Weight Loss Identification

This example describes how multiple types of data acquired on a singlepet, longitudinally, were be leveraged to identify significant and/orunexpected changes in pet health and wellness based on the assessment ofeach data types trends over time when compared to one another.

Methods

Several devices were used in a typical animal-owning home environment toacquire specific data about a standard poodle named Frasier. Each deviceleveraged technologies to acquire and transmit data from the animalacross a home wireless network to the “cloud” where it was stored andanalyzed. Once analyzed, the data was then made available to the animalowner to view through a secure web-site (User Interface, “UI”) on acomputer or smart device with Internet access. The devices utilizedrechargeable batteries and/or connectivity to standard householdelectrical outlets to ensure data was acquired on the animalcontinuously over an extended period of time.

The type of data acquired determined how that data was presented in theUI. For example, dog weight in the UI represents the average of alldaily weights acquired by the scale each day. Food and water consumptionshown in the UI represents the total net weight (in ounces) of eachconsumed in a day. Activity levels were defined as distance travelled ina day based on accelerometer data acquired through a dog collar device.

Materials

In this case, three separate devices were used to acquire specific dataabout Frasier; 1) a collar-mounted device including an accelerometerused to track activity levels, 2) a device that tracks food and waterconsumption from Frasier's food and water bowls using standard loadcells and 3) a 2′×3′ scale device that tracks Frasier's weight usingload cells.

While it is normal for animals to receive food and water outside oftheir food and water bowls, it was assumed that most animal owners tendto be relatively consistent in their feeding and hydration patterns foranimals outside of their normal food and water bowls, which makes thatbehavior constant over time. Also, in this case, the scale used wasplaced in front of the food and water bowls, which ensured Frasier'sweight was recorded each time he ate/drank from the these bowls.Frasier's weight could also be captured by placing the scale anywhere inthe home where he would be motionless for some period of time on aregular bases (such as under a dog bed, dog crate, etc.).

Once each of the devices was positioned in the home and connected to thehome wireless network, Frasier's profile was created in the UI and powerwas maintained with each of the devices, whereby the data that wasacquired from each device flowed through the technical architecture tothe UI where the data could be viewed by the pet owner at any time.Views of the data could be manipulated through the UI to enable dataviews across multiple time horizons (daily, weekly, monthly, yearly, alldata, etc.).

Results

When observing Frasier's data over a 4 week period (FIGS. 15-18 ), itwas clear that 3 of the 4 data stream trends being tracked remainedrelatively stable during this period. It was also observed that hisweight reduced significantly during this period (from a high of 80.3 lbsto a low of 78.8 lbs (FIG. 18 )). This represented a 1.9% decrease intotal body weight during this period which can be significant especiallygiven the consistent negative trend in weight that was observed duringthis time period. To put this in perspective, this rate of decreaseextrapolated over a single year would represent almost a loss of nearlyone-fourth the total body weight which, intuitively, represents anunhealthy weight loss.

It could be possible for this level of weight loss to be attributed toother factors such as increased activity levels and/or changes in foodand water consumption levels. In this case, the ability to observe othertypes of data on Frasier during the same time further highlights thepotential for concern over his weight loss. In this case, it wasobserved that food and water consumption trends remain relativelyconstant, as does Frasier's level of activity (all within normal rangesof variability). As a result of these other data types, one would notexpect to see such a significant decrease in total body weight duringthis period.

This example highlights how the ability to acquire and view a animal'sdata over an extended period of time can identify insights intopotential health and wellness concerns that might not be obvious to thepet owner. If Frasier's weight had been the only data tracked, it couldhave been possible to overlook the significance of the weight change bynot seeing actual food/water consumption and activity data. The abilityto see multiple, relevant data types on a single animal, longitudinally,provided surprising insight into our ability to analyze and assesschanges in the data that might indicate changes in relative trends thatcan identify the potential of increased levels of risk to the petshealth and wellness.

In Frasier's case, a trip to the veterinarian at the end of this testperiod resulted in a series of tests that concluded that Frasier was ina relatively advanced stage of cancer of the lymph nodes. While thisdata led to a diagnosis that afforded him the opportunity to receivetreatment for his cancer, he lived only about 7 months following thisdiagnosis. Had this data been tracked on Frasier much earlier, relativechanges in the data could have been identified earlier that would haveled to an earlier cancer diagnosis and, subsequently, a better outcome;more time and/or options for treatment and/or increased opportunity fora resolution to the disease or to extending his lifespan.

Examples 2A and 2B—Cat Elimination Behavior Tracking

The following two examples detail how data acquisition leveraging sensortechnologies can be used with cats to gain early insights into changesin elimination behavior patterns, that aren't visible to cat owners, butwhich can enable insights into increased risks associated with the earlyonset symptoms of common diseases that impact the length and quality oflife of cats such as diabetes, leukemia, kidney disease, etc. While thetypes of data acquired in each of the following cases is identical, themethods of data acquisition were different, illustrating how differentsensing technologies can be used to capture relevant data.

Example 2A—Weight Sensing

Methods

This example describes a case where a prototype weight-sensing devicewas placed under a cat litter box in a typical cat-owning homeenvironment to acquire specific data about a cat. The device usedmotion/movement detection technology to acquire data from the cat'sengagement of the litter box and stored that data on the device, whichwas subsequently connected to a laptop/pc for data export and analysisusing a standard data analysis tool. FIGS. 19-23 are illustrations ofthe data acquired for a single cat using a single litter box in atypical home environment.

The type of data acquired in this case was the presence (or absence) ofweight in a litter box beyond the normal weight of the box plus thelitter in the box. The presence of additional weight indicated catactivity in the litter box. When the cat was not present in the litterbox, no change in weight was detected. However, as soon as the cat putweight on/in the litter box an engagement event was initiated. The endof an event is identified by time-stamp once the weight of the cat is nolonger measured by the device. Knowing the start/stop time of each eventenables the calculation of event frequency, event duration and litterbox use-patterns in the case of multiple litter boxes existing in asingle home (in this case, only one litter box was used for datacollection purposes but extending the analysis of data to includemultiple litter boxes and even multiple cats is an intuitive extensionof this case that can be realized leveraging the same technologies asdescribed in this case).

Materials

For simplicity, in this case only one device was used to acquirespecific data about a single house cat in a normal home environment. Thedevice consisted of a metal platform upon which the litter box wasplaced. On one end, the platform was slightly elevated by an adjustablespring that enabled one end of the platform with litter box and litterto be raised or lowered slightly. Underneath the platform was a smallbase that included a “contact” post attached to a standard USBdata-writer. When properly adjusted the platform was elevated ⅛″ to ½″above the contact post with only the litter-filled litter box on theplatform. When properly adjusted, the cat entering the litter boxcompressed the spring due to the cats weight being added to the systemmaking contact with contact post. This contact closed a circuit thattriggered a data point and date/time stamp to be written to thedata-writer device signifying the start of an event. As the cat moved inthe litter box, a properly tensioned spring would cause the contactbetween the platform and contact post to be broken and re-established,writing a series of data points over time to the data-writer thatconfirm event activity is continuing in the litter box. When the catleft the litter box, the spring tension broken the connection betweenthe platform and connection post which then stayed broken indicating theend of the litter box engagement event.

This test can be easily extended, utilizing the same device andtechnologies, to include multiple litter boxes and multiple cats in asingle home. This would expand the data analysis to include tracking theindividual litter box engagement patterns of each cat as a measure ofnormal behaviors and changes to normal behaviors which can besignificant. In the case of multiple cats in a home, the system must beable to discern which cat is responsible for each litter box engagementevent, which can be accomplished in a variety of ways including RFID orBluetooth Low Energy (BLE) tags on the cat collar or through developmentof algorithms capable of identifying cats uniquely based on “signature”patterns in the data acquired.

At any point in time, the data files in the data-writer could beconnected to a laptop/pc via USB connection and the files imported intoMS Excel or other data analysis tools to manually track event frequency,duration and time of day patterns and their changes over time.

Results

The data described FIGS. 19-23 was collected on a single cat using asingle litter box over multiple days. While no software-based algorithmsor analytics were designed into the prototype system that acquired thisdata, observation and manual analysis of the data clearly illustrate theability to identify litter box engagement patterns such as eventfrequency, duration and time-of-day patterns and the level ofvariability that exists within and across these measures.

The data in FIG. 19 describes activity in the litter box over sevendays. When each litter box engagement day's data is plotted on a 24 hourtime scale, normal use patterns of both frequency and duration becomeevident, as well as, variability in patterns which could signifynegative trends in health including the possibility of early diseasesymptom onset. Among the interesting features of this data set is how itcan be used to illustrate changes in cat elimination behavior patternsas a result of non-normal external stimuli on the cat. For example, onJuly 4th, the litter box engagement pattern of the cat seems normalduring the day but is unusually low in the evening when compared toother nights. This happened to be an evening when fireworks were beingset off at the next house in celebration of the 4th of July holiday,causing the cat to stay hidden. Another example illustrated by this datais seen on July 9th. On this day, the frequency of elimination, whilelow, falls within the normal range of variability but the total durationof activity for this day was significantly less than any other dayduring this test period (6 minutes of total activity this day comparedto 12-25 minutes of activity every other day). This day was unique forthe cat as its home owner hosted a large dinner party for 30-40 gueststhat afternoon/evening and there was therefore an unusual amount ofactivity in the home throughout the day in before/during/after thatbrought many visitors into the home throughout the day who wereunfamiliar to the cat. As a result, the cat's litter box engagementpattern was impacted by significantly reducing the amount of time spentin the litter box during each event in order to avoid/hide from theunusual activity in the home that day. The following day (July 10th),the cat spent a significantly greater time in the litter box thannormal.

FIGS. 17-18 illustrate the opportunity to leverage this data to identifyadditional metrics that may be of value in assessing cat eliminationbehavior patterns and changes to patterns that may be of significance.In this case, the data can be shown to also identify patterns of normallitter box usage in terms of time of day patterns and cumulativeduration patterns during certain times of day. In addition to eventfrequency and duration, it is likely that changes to time of day usagepatterns in the litter box can be used to identify periods of stress orchanges in health and wellness from the cats normal baseline. In thecase of a multiple litter box home it is also likely that changes in boxchoice patterns over time can be used to identify significant changes inbehavior which may indicate significant changes in cat behavior. In thecase of a multiple cat and/or multiple litter box home, it is alsolikely that changes in cat behavior patterns relative to one another canbe compared to gain new insights into individual cat behavior patternsof interest, as well as, to gain understanding into normal interactionsbetween cats in a home and changes to those patterns that may be ofimportance.

Example 2A—Motion/Movement Sensing

This example describes how data acquisition leveraging sensortechnologies can be used with cats to gain early insights into changesin elimination behavior patterns that are not visible to cat owners, butwhich can enable insights into increased risks associated with the earlyonset symptoms of common diseases that impact the length and quality oflife of cats such as diabetes, leukemia, kidney disease, etc.

Methods

This example describes a case where a motion/movement detection devicewas placed on a cat litter box in a typical cat-owning home environmentto acquire specific data about a cat. The device used motion/movementdetection technology to acquire and transmit data from the litter boxand across a home wireless network to the “cloud” where it was storedand analyzed. Once analyzed, the data was them made available to the catowner to view through a secure web-site (User Interface, “UI”) on anycomputer or smart device with internet access. The device usedrechargeable batteries and/or connectivity to standard householdelectrical outlets to ensure data was acquired on this animalcontinuously over an extended period of time.

The type of data acquired in this case was motion (or lack of motion) ina litter box, which was in turn used as an indicator of cat activity inthe litter box. When the cat was not present in the litter box, nomotion was detected. However, as soon as the cat touched the litter boxthe sensor recognizes motion which, indicates the start of a litter boxengagement event by the cat. During the event, there may be shortperiods of time when motion is/isn't detected, but the event terminationcan be clearly seen when motion data ceases to be acquired for anextended period of time. The start and stop of each litter boxengagement event is time-stamped by the system which enables thecalculation of event frequency, event duration and litter boxuse-patterns in the case of multiple litter boxes existing in a singlehome (in this case, only one litter box was used for data collectionpurposes but extending the analysis of data to include multiple litterboxes and even multiple cats is an intuitive extension of this case thatcan be realized using the same technologies as described in this case).

Materials

For simplicity, in this case only one (1) device was used to acquirespecific data about a single house cat in a normal home environment. Thedevice used included a standard accelerometer sensor and othercomponentry that enabled the ability to acquire, store and transmitrelevant data. The components were housed in a plastic case measuringapproximately 2″ deep×3″ height×6″ depth and attached to any standardlitter box using a heavy duty double stick Velcro® tape. The device wasconnected to normal household electrical power but was also designed sothat it could also be powered by re-chargeable battery.

This test can be easily extended, leveraging the same technologies, toinclude multiple litter boxes and multiple cats in a single home. Thiswould expand the data analysis to include tracking the individual litterbox engagement patterns of each cat as a measure of normal behaviors andchanges to normal behaviors which can be significant. In the case ofmultiple cats in a home, the system must be able to discern which cat isresponsible for each litter box engagement event which can beaccomplished in a variety of ways such as RFID or Bluetooth Low Energy(BLE) tags on the cat collar or through development of algorithmscapable of identifying cats uniquely based on “signature” patterns inthe data acquired.

Once the device was set-up in the home and connected to the homewireless network, the cat's profile was created in the UI, power wasprovided to the device, and the data that was acquired flowed throughthe technical architecture to the UI where the data could be viewed bythe cat owner at any time. Views of the data could be manipulatedthrough the UI to enable data views across multiple time horizons(daily, weekly, monthly, yearly, all data, etc).

Results

The data was collected on a single cat using a single litter box over atwo month period (FIGS. 22 and 23 ). FIG. 22 illustrates the ability toidentify a daily event frequency, as well as to identify themin/max/average time spent in the litter box per event for that day.FIG. 23 illustrates the ability to track each event uniquely during agiven day. While no software-based algorithms or analytics were designedinto the prototype system that acquired this data, observation andmanual analysis of the data clearly illustrate the ability to identifylitter box engagement patterns such as event frequency, duration andtime-of-day patterns and the level of variability that exists within andacross these measures. Leveraging existing technologies, the capabilityexists to automate the analysis of this data to develop “normal”baseline behavior patterns and identify changes to these patterns thatcould indicate increased risk of a negative health trend that mightindicate the early onset of a medical condition, disease or health-risk.These patterns could be identified using statistical/mathematical modelsand/or heuristics or common rules accepted or known in veterinary and/oranimal wellness practices.

What is claimed is:
 1. A method of preparing a nutrition, health, and/orwellness recommendation for a cat who uses a litter box, the methodcomprising: (a) collecting data on one or more of a health parameter, adiet parameter, a behavior parameter, or an environmental parameter ofthe cat on at least one of (i) a weight-sensing device placed under thelitter box or (ii) a motion/movement detection device placed under thelitter box, wherein the one or more of a health parameter, a dietparameter, a behavior parameter, and an environmental parametercomprises a first health parameter that is kidney function of the cat;(b) analyzing the data on a processor to track at least one of eventfrequency in the litter box, event duration in the litter box, or timeof day of event in the litter box, wherein the analyzing of the datacomprises developing a baseline behavior pattern regarding use of thelitter box and identifying a change in use of the litter box away fromthe baseline behavior pattern; and (c) providing the nutrition, health,and/or wellness recommendation based upon the analyzed data, wherein therecommendation identifies an increased risk of kidney disease for thecat who uses the litter box.
 2. The method of claim 1, wherein therecommendation is selected from the group consisting of: a change inenvironment; initiating, limiting, or increasing an exercise protocol;administration or cessation of vitamins, supplements or medication;initiating or modifying a training protocol; a nutritional or feedingchange; a veterinary visit; and a combination thereof.
 3. The method ofclaim 1, wherein the health parameter of the cat further comprises asecond health parameter selected from the group consisting of: age; sex;gender; species or breed; body weight; body mass index (BMI); bodycomposition; body temperature; gait force; reproductive aspects; skinand coat condition; cardiovascular system; gastrointestinal function;vision; cognitive health; and combinations thereof.
 4. The method ofclaim 1, wherein the diet parameter of the cat is selected from thegroup consisting of: the cat's food and water consumption and amount andtime of day thereof; nutritional profile of the food consumed; vitamin,supplement, and/or medication consumption; and combinations thereof. 5.The method of claim 1, wherein the behavior parameter of the cat isselected from the group consisting of: the cat's activity profiles;elimination activity; vocalization; and combinations thereof.
 6. Themethod of claim 1, wherein the environmental parameter of the cat isselected from the group consisting of: weather information; locationcoordinates of cat; location coordinates of food/water/wastecontainer/sleeping or resting locations; presence or absence ofowner/caretaker at the location; presence or absence of children/elderlyat the location; and combinations thereof.
 7. The method of claim 1,wherein: the data identifies, at a plurality of times, a presence orabsence of weight in the litter box beyond a total weight of the litterbox and litter in the litter box; and the at least one of eventfrequency, event duration, or time of day of event is based on thepresence or absence of weight in the litter box beyond the total weightof the litter box and the litter in the litter box at the plurality oftimes.
 8. The method of claim 1, wherein the analyzing of the dataidentifies changes to time of day usage patterns for the litter box. 9.The method of claim 1, wherein the analyzing of the data tracks eventfrequency in the litter box, event duration in the litter box, and timeof day of event in the litter box, and further tracks distribution oflitter box activity.
 10. A method of treating an increased risk ofleukemia or kidney disease for a cat who uses a litter box, the methodcomprising: (a) collecting data on one or more of a health parameter, adiet parameter, a behavior parameter, or an environmental parameter ofthe cat, on at least one of (i) a weight-sensing device placed under thelitter box or (ii) a motion/movement detection device placed under thelitter box, wherein the one or more of a health parameter, a dietparameter, a behavior parameter, and an environmental parametercomprises a first health parameter that is kidney function of the cat;(b) analyzing the data on a processor to track at least one of eventfrequency in the litter box, event duration in the litter box, or timeof day of event in the litter box, wherein the analyzing of the datacomprises developing a baseline behavior pattern regarding use of thelitter box and identifying a change in use of the litter box away fromthe baseline behavior pattern; and (c) providing a nutrition, health,and/or wellness recommendation based on the analyzed data, wherein therecommendation identifies the increased risk of kidney disease for thecat who uses the litter box.
 11. The method of claim 10, furthercomprising administration or cessation of vitamins, supplements, ormedication to the cat having the increased risk of kidney disease,according to the recommendation.